Multihop/Direct Forwarding (MDF) for static wireless sensor networks

Author:

Deng Jing1

Affiliation:

1. University of North Carolina at Greensboro, Greensboro, NC

Abstract

The success of Wireless Sensor Networks (WSNs) depends largely on efficient information delivery from target areas toward data sinks. The problem of data forwarding is complicated by the severe energy constraints of sensors in WSNs. In this work, we propose and analyze a data forwarding scheme, termed Multihop/Direct Forwarding (MDF), for WSNs where sensor nodes forward data traffic toward a common data sink. In the MDF scheme, a node splits outgoing traffic into at most two branches: one is sent to a node that is h units away; the other is sent directly to the data sink. The value of h is chosen to minimize the overall energy consumption of the network. The direct transmission is employed to balance the energy consumption of nodes at different locations and to avoid the so-called hot spot problem in data forwarding. In order to calculate its traffic splitting ratio, a node only needs to know the distance toward the common data sink and that of the farthest node. Our analytical and simulation results show that the MDF scheme performs close to, in terms of energy efficiency and network lifetime, the optimum data forwarding rules, which are more complex and computation intensive.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Cited by 37 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. WALDO: Future Video Synthesis using Object Layer Decomposition and Parametric Flow Prediction;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

2. Implicit Temporal Modeling with Learnable Alignment for Video Recognition;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

3. Revisiting the Parameter Efficiency of Adapters from the Perspective of Precision Redundancy;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

4. Large Selective Kernel Network for Remote Sensing Object Detection;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

5. Collaborative Spatial-Temporal Modeling for Language-Queried Video Actor Segmentation;2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2021-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3